Several lines of evidence have connected the benzodiazepine (BZ) receptor with either the mechanism of action of alcohol or as a potential monitor of the neurotoxic effects associated with alcoholism. Benzodiazepines show cross-tolerance and cross-dependence with alcohol. Inverse agonists at the BZ receptor reverse some alcohol-induced behaviors in rodents. Finally, postmortem studies of the brains of chronic alcoholic patients have shown reduced BZ receptor density and a loss of neurons. Despite these developments, clinical investigations of the function of the BZ system have been difficult to design, primarily because of the inability to identify variables measurable in living human subjects which reflect central BZ receptor function. Functional imaging studies of the BZ receptor may be useful in both clinical and basic science studies related to alcoholism. Functional brain imaging with single photon emission computed tomography (SPECT) is a technique for noninvasively examining brain biochemistry in the living organism. We have developed methods in humans for quantification of the benzodiazepine receptor with SPECT, to estimate the binding potential (Bmax/Kd), by application of modeling under kinetic and equilibrium conditions. The goal of this project is to compare healthy subjects and alcoholics using the equilibrium method and to evaluate the ability of tomographic imaging to measure quantitative changes in the benzodiazepine receptor population in vivo by SPECT. We propose to use the benzodiazepine antagonist iomazenil (Ro 16-0154) radiolabeled with 123(I) for SPECT imaging. This compound binds reversibly with high affinity and specificity to the central type benzodiazepine receptor and the radiolabeled agent has excellent properties for in vivo imaging: high brain uptake and favorable absorbed radiation dose. The focus of this proposal is to rigorously test the following hypothesis: 1) Will alcoholic patients have reduced regional values compared to health subjects after correction for grey matter atrophy using MRI segmentation?